Results for 'intelligibility of explanation'

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  1. The Explanatory Gap Account and Intelligibility of Explanation.Daniel Kostic - 2011 - Theoria 54 (3):27-42.
    This paper examines the explanatory gap account. The key notions for its proper understanding are analysed. In particular, the analysis is concerned with the role of “thick” and “thin” modes of presentation and “thick” and “thin” concepts which are relevant for the notions of “thick” and “thin” conceivability, and to that effect relevant for the gappy and non-gappy identities. The last section of the paper discusses the issue of the intelligibility of explanations. One of the conclusions is that the (...)
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  2. Intelligibility is Necessary for Scientific Explanation, but Accuracy May Not Be.Mike Braverman, John Clevenger, Ian Harmon, Andrew Higgins, Zachary Horne, Joseph Spino & Jonathan Waskan - 2012 - In Naomi Miyake, David Peebles & Richard Cooper (eds.), Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society. Cognitive Science Society.
    Many philosophers of science believe that empirical psychology can contribute little to the philosophical investigation of explanations. They take this to be shown by the fact that certain explanations fail to elicit any relevant psychological events (e.g., familiarity, insight, intelligibility, etc.). We report results from a study suggesting that, at least among those with extensive science training, a capacity to render an event intelligible is considered a requirement for explanation. We also investigate for whom explanations must be capable (...)
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  3. Legitimacy, Authority, and the Political Value of Explanations.Seth Lazar - manuscript
    Here is my thesis (and the outline of this paper). Increasingly secret, complex and inscrutable computational systems are being used to intensify existing power relations, and to create new ones (Section II). To be all-things-considered morally permissible, new, or newly intense, power relations must in general meet standards of procedural legitimacy and proper authority (Section III). Legitimacy and authority constitutively depend, in turn, on a publicity requirement: reasonably competent members of the political community in which power is being exercised must (...)
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  4. Ethics of Artificial Intelligence and Robotics.Vincent C. Müller - 2020 - In Edward N. Zalta (ed.), Stanford Encylopedia of Philosophy. pp. 1-70.
    Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used (...)
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  5. Why a right to explanation of automated decision-making does not exist in the General Data Protection Regulation.Sandra Wachter, Brent Mittelstadt & Luciano Floridi - 2017 - International Data Privacy Law 1 (2):76-99.
    Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In contrast (...)
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  6. Ethics of Artificial Intelligence.Vincent C. Müller - 2021 - In Anthony Elliott (ed.), The Routledge Social Science Handbook of Ai. Routledge. pp. 122-137.
    Artificial intelligence (AI) is a digital technology that will be of major importance for the development of humanity in the near future. AI has raised fundamental questions about what we should do with such systems, what the systems themselves should do, what risks they involve and how we can control these. - After the background to the field (1), this article introduces the main debates (2), first on ethical issues that arise with AI systems as objects, i.e. tools made and (...)
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  7. Understanding, explanation, and intelligibility: Henk de Regt: Understanding scientific understanding. Oxford: Oxford University Press, 2017, xii+301pp, £ 47.99HB. [REVIEW]Insa Lawler - 2018 - Metascience (1):57-60.
    Review of Henk de Regt's "Understanding Scientific Understanding".
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  8. Aspects of Sex Differences: Social Intelligence vs. Creative Intelligence.Ferdinand Fellmann & Esther Redolfi Widmann - 2017 - Advances in Anthropology 7:298-317.
    In this article, we argue that there is an essential difference between social intelligence and creative intelligence, and that they have their foundation in human sexuality. For sex differences, we refer to the vast psychological, neurological, and cognitive science research where problem-solving, verbal skills, logical reasoning, and other topics are dealt with. Intelligence tests suggest that, on average, neither sex has more general intelligence than the other. Though people are equals in general intelligence, they are different in special forms of (...)
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  9. How to create a life or mind as the explanation of our consciousness, intelligence and language.Xinyan Zhang - 2022 - Journal of Neurophilosophy (No. 2 (2022)).
    Against ideas of dualism, logocentrism, anthropocentrism, animism, panpsychism, biocentrism, neurocentrism, foundationalism, computationalism, especially substantialism, reductionism and even physicalism, the author argues that life may be the only non-reductive concept, even the only ontological concept, with which we may explain our consciousness, intelligence and language. Life, as defined in this article, explains but not only human brains, and even not only biological organisms. Still, the mind, also as defined in this article, is the only one it explains. No mind may exist (...)
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  10. The Artificial Intelligence Explanatory Trade-Off on the Logic of Discovery in Chemistry.José Ferraz-Caetano - 2023 - Philosophies 8 (2):17.
    Explanation is a foundational goal in the exact sciences. Besides the contemporary considerations on ‘description’, ‘classification’, and ‘prediction’, we often see these terms in thriving applications of artificial intelligence (AI) in chemistry hypothesis generation. Going beyond describing ‘things in the world’, these applications can make accurate numerical property calculations from theoretical or topological descriptors. This association makes an interesting case for a logic of discovery in chemistry: are these induction-led ventures showing a shift in how chemists can problematize research (...)
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  11. Explaining Explanations in AI.Brent Mittelstadt - forthcoming - FAT* 2019 Proceedings 1.
    Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These models are a useful pedagogical device for teaching trained professionals how to predict what decisions will be made by the complex system, and most importantly how the system might break. However, when considering any such model it’s important to remember Box’s maxim that "All models are wrong but some are useful." We focus on (...)
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  12. Triple definition or explanation of consciousness.Xinyan Zhang - manuscript
    The author argues that consciousness may never be defined or explained with entities or their properties, neither with brains, neurons, and biomacromolecules, nor with particles, waves, and fields. Instead, the author proposes a system with matter, energy, and lives as its components, and with all its components defined as changes. Based on the systematic relationships among these three components, a triple definition or explanation of consciousness is reached: • Ontologically, consciousness is universal, since it is the systematic distinction between (...)
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  13. The prospect of artificial-intelligence supported ethics review.Philip J. Nickel - forthcoming - Ethics and Human Research.
    The burden of research ethics review falls not just on researchers, but on those who serve on research ethics committees (RECs). With the advent of automated text analysis and generative artificial intelligence, it has recently become possible to teach models to support human judgment, for example by highlighting relevant parts of a text and suggesting actionable precedents and explanations. It is time to consider how such tools might be used to support ethics review and oversight. This commentary argues that with (...)
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  14. AISC 17 Talk: The Explanatory Problems of Deep Learning in Artificial Intelligence and Computational Cognitive Science: Two Possible Research Agendas.Antonio Lieto - 2018 - In Proceedings of AISC 2017.
    Endowing artificial systems with explanatory capacities about the reasons guiding their decisions, represents a crucial challenge and research objective in the current fields of Artificial Intelligence (AI) and Computational Cognitive Science [Langley et al., 2017]. Current mainstream AI systems, in fact, despite the enormous progresses reached in specific tasks, mostly fail to provide a transparent account of the reasons determining their behavior (both in cases of a successful or unsuccessful output). This is due to the fact that the classical problem (...)
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  15. Narrative explanation.J. David Velleman - 2003 - Philosophical Review 112 (1):1-25.
    A story does more than recount events; it recounts events in a way that renders them intelligible, thus conveying not just information but also understanding. We might therefore be tempted to describe narrative as a genre of explanation. When the police invite a suspect to “tell his story,” they are asking him to explain the blood on his shirt or his absence from home on the night of the murder; and whether he is judged to have a “good story” (...)
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  16. ANNs and Unifying Explanations: Reply to Erasmus, Brunet, and Fisher.Yunus Prasetya - 2022 - Philosophy and Technology 35 (2):1-9.
    In a recent article, Erasmus, Brunet, and Fisher (2021) argue that Artificial Neural Networks (ANNs) are explainable. They survey four influential accounts of explanation: the Deductive-Nomological model, the Inductive-Statistical model, the Causal-Mechanical model, and the New-Mechanist model. They argue that, on each of these accounts, the features that make something an explanation is invariant with regard to the complexity of the explanans and the explanandum. Therefore, they conclude, the complexity of ANNs (and other Machine Learning models) does not (...)
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  17. Social intelligence: How to integrate research? A mechanistic perspective.Marcin Miłkowski - 2019 - AI and Society 34 (4):735-744.
    Is there a field of social intelligence? Many various disciplines approach the subject and it may only seem natural to suppose that different fields of study aim at explaining different phenomena; in other words, there is no special field of study of social intelligence. In this paper, I argue for an opposite claim. Namely, there is a way to integrate research on social intelligence, as long as one accepts the mechanistic account to explanation. Mechanistic integration of different explanations, however, (...)
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  18. ITSB: An Intelligent Tutoring System Authoring Tool.Samy S. Abu Naser - 2016 - Journal of Scientific and Engineering Research 3 (5):63-71.
    Abstract. Intelligent Tutoring System Builder (ITSB) is an authoring tool designed and developed to aid teachers in constructing intelligent tutoring systems in a multidisciplinary fields. The teacher is needed to create a set of pedagogical fundamentals, which, in line, are inured to automatically build up a broad tutor framework and construct an intelligent tutoring system. In this paper an explanation of the theory and the architecture of the tool is outlined. A presentation of several system components, the requirements of (...)
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  19. Thoughts on Artificial Intelligence and the Origin of Life Resulting from General Relativity, with Neo-Darwinist Reference to Human Evolution and Mathematical Reference to Cosmology.Rodney Bartlett - manuscript
    When this article was first planned, writing was going to be exclusively about two things - the origin of life and human evolution. But it turned out to be out of the question for the author to restrict himself to these biological and anthropological topics. A proper understanding of them required answering questions like “What is the nature of the universe – the home of life – and how did it originate?”, “How can time travel be removed from fantasy and (...)
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  20. Unexplainability and Incomprehensibility of Artificial Intelligence.Roman Yampolskiy - manuscript
    Explainability and comprehensibility of AI are important requirements for intelligent systems deployed in real-world domains. Users want and frequently need to understand how decisions impacting them are made. Similarly it is important to understand how an intelligent system functions for safety and security reasons. In this paper, we describe two complementary impossibility results (Unexplainability and Incomprehensibility), essentially showing that advanced AIs would not be able to accurately explain some of their decisions and for the decisions they could explain people would (...)
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  21. Striking at the Heart of Cognition: Aristotelian Phantasia, Working Memory, and Psychological Explanation.Javier Gomez-Lavin & Justin Humphreys - 2022 - Medicina Nei Secoli: Journal of History of Medicine and Medical Humanities 34 (2):13-38.
    This paper examines a parallel between Aristotle’s account of phantasia and contemporary psychological models of working memory, a capacity that enables the temporary maintenance and manipulation of information used in many behaviors. These two capacities, though developed within two distinct scientific paradigms, share a common strategy of psychological explanation, Aristotelian Faculty Psychology. This strategy individuates psychological components by their target-domains and functional roles. Working memory and phantasia result from an attempt to individuate the psychological components responsible for flexible thought (...)
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  22. Social intelligence: how to integrate research? A mechanistic perspective.Marcin Miłkowski - 2014 - Proceedings of the European Conference on Social Intelligence (ECSI-2014).
    Is there a field of social intelligence? Many various disciplines ap-proach the subject and it may only seem natural to suppose that different fields of study aim at explaining different phenomena; in other words, there is no spe-cial field of study of social intelligence. In this paper, I argue for an opposite claim. Namely, there is a way to integrate research on social intelligence, as long as one accepts the mechanistic account to explanation. Mechanistic inte-gration of different explanations, however, (...)
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  23. Understanding Biology in the Age of Artificial Intelligence.Adham El Shazly, Elsa Lawerence, Srijit Seal, Chaitanya Joshi, Matthew Greening, Pietro Lio, Shantung Singh, Andreas Bender & Pietro Sormanni - manuscript
    Modern life sciences research is increasingly relying on artificial intelligence (AI) approaches to model biological systems, primarily centered around the use of machine learning (ML) models. Although ML is undeniably useful for identifying patterns in large, complex data sets, its widespread application in biological sciences represents a significant deviation from traditional methods of scientific inquiry. As such, the interplay between these models and scientific understanding in biology is a topic with important implications for the future of scientific research, yet it (...)
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    On Functionalism's Context-Dependent Explanations of Mental States.Hong Joo Ryoo - manuscript
    This paper integrates type functionalism with the Kairetic account to develop context-specific models for explaining mental states, particularly pain, across different species and systems. By employing context-dependent mapping f_c, we ensure cohesive causal explanations while accommodating multiple realizations of mental states. The framework identifies context subsets C_i and maps them to similarity subspaces S_i, capturing the unique physiological, biochemical, and computational mechanisms underlying pain in different entities such as humans, octopi, and AI systems. This approach highlights the importance of causal (...)
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  25. Local explanations via necessity and sufficiency: unifying theory and practice.David Watson, Limor Gultchin, Taly Ankur & Luciano Floridi - 2022 - Minds and Machines 32:185-218.
    Necessity and sufficiency are the building blocks of all successful explanations. Yet despite their importance, these notions have been conceptually underdeveloped and inconsistently applied in explainable artificial intelligence (XAI), a fast-growing research area that is so far lacking in firm theoretical foundations. Building on work in logic, probability, and causality, we establish the central role of necessity and sufficiency in XAI, unifying seemingly disparate methods in a single formal framework. We provide a sound and complete algorithm for computing explanatory factors (...)
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  26. The Relations Between Pedagogical and Scientific Explanations of Algorithms: Case Studies from the French Administration.Maël Pégny - manuscript
    The opacity of some recent Machine Learning (ML) techniques have raised fundamental questions on their explainability, and created a whole domain dedicated to Explainable Artificial Intelligence (XAI). However, most of the literature has been dedicated to explainability as a scientific problem dealt with typical methods of computer science, from statistics to UX. In this paper, we focus on explainability as a pedagogical problem emerging from the interaction between lay users and complex technological systems. We defend an empirical methodology based on (...)
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  27. What is wrong with intelligent design?Gregory W. Dawes - 2007 - International Journal for Philosophy of Religion 61 (2):69 - 81.
    While a great deal of abuse has been directed at intelligent design theory (ID), its starting point is a fact about biological organisms that cries out for explanation, namely "specified complexity" (SC). Advocates of ID deploy three kind of argument from specified complexity to the existence of a designer: an eliminative argument, an inductive argument, and an inference to the best explanation. Only the first of these merits the abuse directed at it; the other two arguments are worthy (...)
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  28. What we owe to decision-subjects: beyond transparency and explanation in automated decision-making.David Gray Grant, Jeff Behrends & John Basl - 2023 - Philosophical Studies 2003:1-31.
    The ongoing explosion of interest in artificial intelligence is fueled in part by recently developed techniques in machine learning. Those techniques allow automated systems to process huge amounts of data, utilizing mathematical methods that depart from traditional statistical approaches, and resulting in impressive advancements in our ability to make predictions and uncover correlations across a host of interesting domains. But as is now widely discussed, the way that those systems arrive at their outputs is often opaque, even to the experts (...)
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  29. Artificial Intelligence, Phenomenology, and the Molyneux Problem.Chris A. Kramer - 2023 - The Philosophy of Humor Yearbook 4 (1):225-226.
    This short article is a “conversation” in which an android, Mort, replies to Richard Marc Rubin’s android named Sol in “The Robot Sol Explains Laughter to His Android Brethren” (The Philosophy of Humor Yearbook, 2022). There Sol offers an explanation for how androids can laugh--largely a reaction to frustration and unmet expectations: “my account says that laughter is one of four ways of dealing with frustration, difficulties, and insults. It is a way of getting by. If you need to (...)
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  30. St. Thomas Aquinas on Intelligent Design.Robert C. Koons & Logan Paul Gage - 2011 - Proceedings of the American Catholic Philosophical Association 85:79-97.
    Recently, the Intelligent Design (ID) movement has challenged the claim of many in the scientific establishment that nature gives no empirical signs of having been deliberately designed. In particular, ID arguments in biology dispute the notion that neo-Darwinian evolution is the only viable scientific explanation of the origin of biological novelty, arguing that there are telltale signs of the activity of intelligence which can be recognized and studied empirically. In recent years, a number of Catholic philosophers, theologians, and scientists (...)
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  31. A Theory of Practical Meaning.Carlotta Pavese - 2017 - Philosophical Topics 45 (2):65-96.
    This essay is divided into two parts. In the first part (§2), I introduce the idea of practical meaning by looking at a certain kind of procedural systems — the motor system — that play a central role in computational explanations of motor behavior. I argue that in order to give a satisfactory account of the content of the representations computed by motor systems (motor commands), we need to appeal to a distinctively practical kind of meaning. Defending the explanatory relevance (...)
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  32. Facing Janus: An Explanation of the Motivations and Dangers of AI Development.Aaron Graifman - manuscript
    This paper serves as an intuition building mechanism for understanding the basics of AI, misalignment, and the reasons for why strong AI is being pursued. The approach is to engage with both pro and anti AI development arguments to gain a deeper understanding of both views, and hopefully of the issue as a whole. We investigate the basics of misalignment, common misconceptions, and the arguments for why we would want to pursue strong AI anyway. The paper delves into various aspects (...)
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  33. Contenu, enjeux et diversité des acceptions de l’Intelligent Design en contexte étatsunien.Philippe Gagnon - 2007 - Connaître. Cahiers de l'Association Foi Et Culture Scientifique 26:9-43.
    This paper aims at introducing a French audience to the Intelligent Design debate. It starts by reviewing recent attacks on any possibility of a rational account of theism in light of the contemporary theory of evolution. A section is devoted to outlining the genesis of the "wedge" strategy, to distinguish it from young earth creationism, and to highlight the questioning of evolution as our meta-narrative bearing on overall conceptions of the scientific endeavor. The arguments propounded by Behe are reviewed in (...)
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  34. The Pragmatic Turn in Explainable Artificial Intelligence (XAI).Andrés Páez - 2019 - Minds and Machines 29 (3):441-459.
    In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies (...)
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  35. From Life-Like to Mind-Like Explanation: Natural Agency and the Cognitive Sciences.Alex Djedovic - 2020 - Dissertation, University of Toronto, St. George Campus
    This dissertation argues that cognition is a kind of natural agency. Natural agency is the capacity that certain systems have to act in accordance with their own norms. Natural agents are systems that bias their repertoires in response to affordances in the pursuit of their goals. Cognition is a special mode of this general phenomenon. Cognitive systems are agents that have the additional capacity to actively take their worlds to be certain ways, regardless of whether the world is really that (...)
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  36. From Life-Like to Mind-Like Explanation: Natural Agency and the Cognitive Sciences.Alex Djedovic - 2020 - Dissertation, University of Toronto, St. George Campus
    This dissertation argues that cognition is a kind of natural agency. Natural agency is the capacity that certain systems have to act in accordance with their own norms. Natural agents are systems that bias their repertoires in response to affordances in the pursuit of their goals. -/- Cognition is a special mode of this general phenomenon. Cognitive systems are agents that have the additional capacity to actively take their worlds to be certain ways, regardless of whether the world is really (...)
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  37. May Artificial Intelligence Be a Co-Author on an Academic Paper?Ayşe Balat & İlhan Bahşi - 2023 - European Journal of Therapeutics 29 (3):e12-e13.
    Dear Colleagues, -/- Recently, for an article submitted to the European Journal of Therapeutics, it was reported that the paper may have been written with artificial intelligence support at a rate of more than 50% in the preliminary examination made with Turnitin. However, the authors did not mention this in the article’s material method or explanations section. Fortunately, the article’s out-of-date content and fundamental errors in its methodology allowed us no difficulty making the desk rejection decision. -/- On the other (...)
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  38. Moral Perspective from a Holistic Point of View for Weighted DecisionMaking and its Implications for the Processes of Artificial Intelligence.Mina Singh, Devi Ram, Sunita Kumar & Suresh Das - 2023 - International Journal of Research Publication and Reviews 4 (1):2223-2227.
    In the case of AI, automated systems are making increasingly complex decisions with significant ethical implications, raising questions about who is responsible for decisions made by AI and how to ensure that these decisions align with society's ethical and moral values, both in India and the West. Jonathan Haidt has conducted research on moral and ethical decision-making. Today, solving problems like decision-making in autonomous vehicles can draw on the literature of the trolley dilemma in that it illustrates the complexity of (...)
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  39. Revisiting Maher’s one-factor theory of delusion.Chenwei Nie - 2023 - Neuroethics 16 (2):1-16.
    How many factors, i.e. departures from normality, are necessary to explain a delusion? Maher’s classic one-factor theory argues that the only factor is the patient’s anomalous experience, and a delusion arises as a normal explanation of this experience. The more recent two-factor theory, on the other hand, contends that a second factor is also needed, with reasoning abnormality being a potential candidate, and a delusion arises as an abnormal explanation of the anomalous experience. In the past few years, (...)
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  40. Learning to Discriminate: The Perfect Proxy Problem in Artificially Intelligent Criminal Sentencing.Benjamin Davies & Thomas Douglas - 2022 - In Jesper Ryberg & Julian V. Roberts (eds.), Sentencing and Artificial Intelligence. Oxford: OUP.
    It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that the (...)
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  41. The rationality of scientific discovery part 1: The traditional rationality problem.Nicholas Maxwell - 1974 - Philosophy of Science 41 (2):123--53.
    The basic task of the essay is to exhibit science as a rational enterprise. I argue that in order to do this we need to change quite fundamentally our whole conception of science. Today it is rather generally taken for granted that a precondition for science to be rational is that in science we do not make substantial assumptions about the world, or about the phenomena we are investigating, which are held permanently immune from empirical appraisal. According to this standard (...)
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  42. The Explanatory Role of Umwelt in Evolutionary Theory: Introducing von Baer's Reflections on Teleological Development.Tiago Rama - 2024 - Biosemiotics 1:1-26.
    Abstract: This paper argues that a central explanatory role for the concept of Umwelt in theoretical biology is to be found in developmental biology, in particular in the effort to understand development as a goal-directed and adaptive process that is controlled by the organism itself. I will reach this conclusion in two (interrelated) ways. The first is purely theoretical and relates to the current scenario in the philosophy of biology. Challenging neo-Darwinism requires a new understanding of the various components involved (...)
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  43. Quine's interpretation problem and the early development of possible worlds semantics.Sten Lindström - 2001 - In Ondrey Majer (ed.), The Logica Yearbook 2000. Filosofia.
    In this paper, I shall consider the challenge that Quine posed in 1947 to the advocates of quantified modal logic to provide an explanation, or interpretation, of modal notions that is intuitively clear, allows “quantifying in”, and does not presuppose, mysterious, intensional entities. The modal concepts that Quine and his contemporaries, e.g. Carnap and Ruth Barcan Marcus, were primarily concerned with in the 1940’s were the notions of (broadly) logical, or analytical, necessity and possibility, rather than the metaphysical modalities (...)
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  44. The Use and Misuse of Counterfactuals in Ethical Machine Learning.Atoosa Kasirzadeh & Andrew Smart - 2021 - In Atoosa Kasirzadeh & Andrew Smart (eds.), ACM Conference on Fairness, Accountability, and Transparency (FAccT 21).
    The use of counterfactuals for considerations of algorithmic fairness and explainability is gaining prominence within the machine learning community and industry. This paper argues for more caution with the use of counterfactuals when the facts to be considered are social categories such as race or gender. We review a broad body of papers from philosophy and social sciences on social ontology and the semantics of counterfactuals, and we conclude that the counterfactual approach in machine learning fairness and social explainability can (...)
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  45. Contesti in intelligenza artificiale: una fugace rassegna (Context in artificial intelligence: a fleeting overview).Varol Akman - 2002 - In Carlo Penco (ed.), La svolta contestuale. New York: McGraw-Hill.
    The notion of context arises in assorted areas of artificial intelligence (AI), including knowledge representation, natural language processing, intelligent information retrieval, etc. Although the term ‘context’ is frequently employed in descriptions, explanations, and analyses of computer programs in these areas, its meaning is frequently left to the reader’s understanding. -/- My aim in this paper is to offer a swift review of context in AI. I will first identify the role of context in various fields of AI. I will then (...)
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  46. The Sirens of Elea: Rationalism, Monism and Idealism in Spinoza.Yitzhak Melamed - 2012 - In Stewart Duncan & Antonia LoLordo (eds.), Debates in Modern Philosophy: Essential Readings and Contemporary Responses. New York: Routledge.
    The main thesis of Michael Della Rocca’s outstanding Spinoza book (Della Rocca 2008a) is that at the very center of Spinoza’s philosophy stands the Principle of Sufficient Reason (PSR): the stipulation that everything must be explainable or, in other words, the rejection of any brute facts. Della Rocca rightly ascribes to Spinoza a strong version of the PSR. It is not only that the actual existence and features of all things must be explicable, but even the inexistence – as well (...)
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  47. Can We Think That Machines Are Conscious? A Survey of Philosophical Problems Facing the Attribution of Consciousness to Machines.Parker Settecase - forthcoming - Journal of Artificial Intelligence and Consciousness.
    In this paper I’ll examine whether we could be justified in attributing consciousness to artificial intelligent systems. First, I’ll give a brief history of the concept of artificial intelligence (AI) and get clear on the terms I’ll be using. Second, I’ll briefly review the kinds of AI programs on offer today, identifying which research program I think provides the best candidate for machine consciousness. Lastly, I’ll consider the three most plausible ways of knowing whether a machine is conscious: (1) an (...)
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  48. Wittgenstein on the Chain of Reasons.Matthieu Queloz - 2016 - Wittgenstein-Studien 7 (1):105-130.
    In this paper, I examine Wittgenstein’s conception of reason and rationality through the lens of his conception of reasons. Central in this context, I argue, is the image of the chain, which informs not only his methodology in the form of the chain-method, but also his conception of reasons as linking up immediately, like the links of a chain. I first provide a general sketch of what reasons are on Wittgenstein’s view, arguing that giving reasons consists in making thought and (...)
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  49. The Formats of Cognitive Representation: A Computational Account.Dimitri Coelho Mollo & Alfredo Vernazzani - 2023 - Philosophy of Science.
    Cognitive representations are typically analysed in terms of content, vehicle and format. While current work on formats appeals to intuitions about external representations, such as words and maps, in this paper we develop a computational view of formats that does not rely on intuitions. In our view, formats are individuated by the computational profiles of vehicles, i.e., the set of constraints that fix the computational transformations vehicles can undergo. The resulting picture is strongly pluralistic, it makes space for a variety (...)
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  50. Spinoza and the Theory of Organism.Hans Jonas - 1965 - Journal of the History of Philosophy 3 (1):43-57.
    In lieu of an abstract, here is a brief excerpt of the content:Spinoza and the Theory of Organism HANS JONAS I CARTESIANDUALISMlanded speculation on the nature of life in an impasse: intelligible as, on principles of mechanics, the correlation of structure and function became within the res extensa, that of structure-plus-function with feeling or experience (modes of the res cogitans) was lost in the bifurcation, and thereby the fact of life itself became unintelligible at the same time that the (...) of its bodily performance seemed to be assured. The impasse became manifest in Occasionalism : its tour de force of an extraneous, divine "synchronization" of the outer and the inner world (the latter denied to animals) not only suffered from its extreme artificiality, the common failing of such ad hoc constructions, but even at so high a cost failed to accomplish its theoretical purpose by its own terms. For the animal machine, like any machine, raises beyond the question of the "how" that of the "what for" of its functioning---of the purpose for which it had thus been constructed by its maker.1 Its performance, however devoid of immanent teleology, must serve an end, and that end must be someone's end. This end may (directly) be itself, as indeed Descartes had implied when declaring self-preservation to be the effect of the functioning of the organic automaton. In that case the existence as such of the machine would be its end--either terminally, or in turn to benefit something else. In the former case, the machine would have to be more than a machine, for a mere machine cannot enioy its existence. But since, by the rigorous conception of the res extensa, it cannot be more than a machine, its function and/or existence must serve something other than itself. Automata in Descartes ' time were mainly for entertainment (rather than work). But the raison d'etre of the living kingdom could not well be seen in God's indulging his mechanical abilities or in the amusement of celestial spectators--especially since mere complexity of arrangement does not create new quality and thus add something to the unrelieved sameness of the simple substratum that might enrich the spectrum of being. For quality, beyond the primitive determinations of the extended per se, is the subjective creature of sensation, the confused representation of quantity in a mind; and thus organisms cannot harbor it because as mere machines they lack mentality, and pure spirits cannot because they lack sensuality, or the privilege of confusion and thereby of illusion with its possible enjoyment. And as to their intellectual enjoyment, even that, deprived of the thrill of discovery by the same token, would pale in the contemplation of what to sufficiently large The concept of "machine," adopted for its strict confinementto efficientcause, is still a finalisticconcept,even thoughthe final cause is no longer internal to the entity, as a mode of its own operation,but external to it as antecedent design. [43] 44 HISTORY OF PHILOSOPHY intellects is nothing but the ever-repeated exemplification of the same few, elementary (and ultimately trivial) truths. There remained, then, the time-honored--Stoic as well as Christian--idea that plants and animals are for the benefit of Man. Indeed, since the existence of a living world is the necessary condition for the existence of any of its members, the self-justifying nature of at least one such member (= species) would justify the existence of the whole. In Stoicism, Man provided this end by his possession of reason, which makes him the culmination of a terrestrial scale of being that is also self-justifying throughout all its grades (the end as the best of many that are good in degrees) ; in Christianity, by his possession of an immortal soul, which makes him the sole imago Dei in creation (the end as the sole issue at stake) ; and Cartesian dualism radicalized this latter position by making man even the sole possessor of inwardness or "soul" of any kind, thus the only one of whom "end" can meaningfully be predicated as he alone can entertain ends. All other life then, the product of physical necessity, can be considered his means. However, this traditional idea, in its anthropocentric vanity never a... (shrink)
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